OpenRaiser/Intern-Atlas huggingface dataset:
GED: the method for group evolution discovery in social networks
Venue: arXiv cs.SI 2012
Year: 2012

The continuous interest in the social network area contributes to the fast development of this field. The new possibilities of obtaining and storing data facilitate deeper analysis of the entire network, extracted social groups and single individuals as well. One of the most interesting research topic is the dynamics of social groups, it means analysis of group evolution over time. Having appropriate knowledge and methods for dynamic analysis, one may attempt to predict the future of the group, and then manage it properly in order to achieve or change this predicted future according to specific needs. Such ability would be a powerful tool in the hands of human resource managers, personnel recruitment, marketing, etc. The social group evolution consists of individual events and seven types of such changes have been identified in the paper: continuing, shrinking, growing, splitting, merging, dissolving and forming. To enable the analysis of group evolution a change indicator - inclusion measure was proposed. It has been used in a new method for exploring the evolution of social groups, called Group Evolution Discovery (GED). The experimental results of its use together with the comparison to two well-known algorithms in terms of accuracy, execution time, flexibility and ease of implementation are also described in the paper.
Empirical review of standard benchmark functions using evolutionary global optimization
Venue: arXiv cs.NE 2012
Year: 2012

We have employed a recent implementation of genetic algorithms to study a range of standard benchmark functions for global optimization. It turns out that some of them are not very useful as challenging test functions, since they neither allow for a discrimination between different variants of genetic operators nor exhibit a dimensionality scaling resembling that of real-world problems, for example that of global structure optimization of atomic and molecular clusters. The latter properties seem to be simulated better by two other types of benchmark functions. One type is designed to be deceptive, exemplified here by Lunacek's function. The other type offers additional advantages of markedly increased complexity and of broad tunability in search space characteristics. For the latter type, we use an implementation based on randomly distributed Gaussians. We advocate the use of the latter types of test functions for algorithm development and benchmarking.
Construction and analysis of polar and concatenated polar codes: practical approach
Venue: arXiv cs.IT 2012
Year: 2012

We consider two problems related to polar codes. First is the problem of polar codes construction and analysis of their performance without Monte-Carlo method. The formulas proposed are the same as those in [Mori-Tanaka], yet we believe that our approach is original and has clear advantages. The resulting computational procedure is presented in a fast algorithm form which can be easily implemented on a computer. Secondly, we present an original method of construction of concatenated codes based on polar codes. We give an algorithm for construction of such codes and present numerical experiments showing significant performance improvement with respect to original polar codes proposed by Arıkan. We use the term \emph{concatenated code} not in its classical sense (e.g. [Forney]). However we believe that our usage is quite appropriate for the exploited construction. Further, we solve the optimization problem of choosing codes minimizing the block error of the whole concatenated code under the constraint of its fixed rate.
Computing n-Gram Statistics in MapReduce
Venue: arXiv cs.IR 2012
Year: 2012

Statistics about n-grams (i.e., sequences of contiguous words or other tokens in text documents or other string data) are an important building block in information retrieval and natural language processing. In this work, we study how n-gram statistics, optionally restricted by a maximum n-gram length and minimum collection frequency, can be computed efficiently harnessing MapReduce for distributed data processing. We describe different algorithms, ranging from an extension of word counting, via methods based on the Apriori principle, to a novel method Suffix-σthat relies on sorting and aggregating suffixes. We examine possible extensions of our method to support the notions of maximality/closedness and to perform aggregations beyond occurrence counting. Assuming Hadoop as a concrete MapReduce implementation, we provide insights on an efficient implementation of the methods. Extensive experiments on The New York Times Annotated Corpus and ClueWeb09 expose the relative benefits and trade-offs of the methods.
NILS: a Neutrality-based Iterated Local Search and its application to Flowshop Scheduling
Venue: arXiv cs.NE 2012
Year: 2012

This paper presents a new methodology that exploits specific characteristics from the fitness landscape. In particular, we are interested in the property of neutrality, that deals with the fact that the same fitness value is assigned to numerous solutions from the search space. Many combinatorial optimization problems share this property, that is generally very inhibiting for local search algorithms. A neutrality-based iterated local search, that allows neutral walks to move on the plateaus, is proposed and experimented on a permutation flowshop scheduling problem with the aim of minimizing the makespan. Our experiments show that the proposed approach is able to find improving solutions compared with a classical iterated local search. Moreover, the tradeoff between the exploitation of neutrality and the exploration of new parts of the search space is deeply analyzed.
Causal relay networks
Venue: arXiv cs.IT 2012
Year: 2012

In this paper, we study causal discrete-memoryless relay networks (DMRNs). The network consists of multiple nodes, each of which can be a source, relay, and/or destination. In the network, there are two types of relays, i.e., relays with one sample delay (strictly causal) and relays without delay (causal) whose transmit signal depends not only on the past received symbols but also on the current received symbol. For this network, we derive two new cut-set bounds, one when the causal relays have their own messages and the other when not. Using examples of a causal vector Gaussian two-way relay channel and a causal vector Gaussian relay channel, we show that the new cut-set bounds can be achieved by a simple amplify-and-forward type relaying. Our result for the causal relay channel strengthens the previously known capacity result for the same channel by El Gamal, Hassanpour, and Mammen.
Appropriate Nouns with Obligatory Modifiers
Venue: arXiv cs.CL 2012
Year: 2012

The notion of appropriate sequence as introduced by Z. Harris provides a powerful syntactic way of analysing the detailed meaning of various sentences, including ambiguous ones. In an adjectival sentence like 'The leather was yellow', the introduction of an appropriate noun, here 'colour', specifies which quality the adjective describes. In some other adjectival sentences with an appropriate noun, that noun plays the same part as 'colour' and seems to be relevant to the description of the adjective. These appropriate nouns can usually be used in elementary sentences like 'The leather had some colour', but in many cases they have a more or less obligatory modifier. For example, you can hardly mention that an object has a colour without qualifying that colour at all. About 300 French nouns are appropriate in at least one adjectival sentence and have an obligatory modifier. They enter in a number of sentence structures related by several syntactic transformations. The appropriateness of the noun and the fact that the modifier is obligatory are reflected in these transformations. The description of these syntactic phenomena provides a basis for a classification of these nouns. It also concerns the lexical properties of thousands of predicative adjectives, and in particular the relations between the sentence without the noun : 'The leather was yellow' and the adjectival sentence with the noun : 'The colour of the leather was yellow'.
The Road to VEGAS: Guiding the Search over Neutral Networks
Venue: arXiv cs.NE 2012
Year: 2012

VEGAS (Varying Evolvability-Guided Adaptive Search) is a new methodology proposed to deal with the neutrality property of some optimization problems. ts main feature is to consider the whole neutral network rather than an arbitrary solution. Moreover, VEGAS is designed to escape from plateaus based on the evolvability of solution and a multi-armed bandit. Experiments are conducted on NK-landscapes with neutrality. Results show the importance of considering the whole neutral network and of guiding the search cleverly. The impact of the level of neutrality and of the exploration-exploitation trade-off are deeply analyzed.
Reduced Complexity Super-Trellis Decoding for Convolutionally Encoded Transmission Over ISI-Channels
Venue: arXiv cs.IT 2012
Year: 2012

In this paper we propose a matched encoding (ME) scheme for convolutionally encoded transmission over intersymbol interference (usually called ISI) channels. A novel trellis description enables to perform equalization and decoding jointly, i.e., enables efficient super-trellis decoding. By means of this matched non-linear trellis description we can significantly reduce the number of states needed for the receiver-side Viterbi algorithm to perform maximum-likelihood sequence estimation. Further complexity reduction is achieved using the concept of reduced-state sequence estimation.
Testing Permanent Oracles -- Revisited
Venue: arXiv cs.DS 2012
Year: 2012

Suppose we are given an oracle that claims to approximate the permanent for most matrices X, where X is chosen from the Gaussian ensemble (the matrix entries are i.i.d. univariate complex Gaussians). Can we test that the oracle satisfies this claim? This paper gives a polynomial-time algorithm for the task. The oracle-testing problem is of interest because a recent paper of Aaronson and Arkhipov showed that if there is a polynomial-time algorithm for simulating boson-boson interactions in quantum mechanics, then an approximation oracle for the permanent (of the type described above) exists in BPP^NP. Since computing the permanent of even 0/1 matrices is #P-complete, this seems to demonstrate more computational power in quantum mechanics than Shor's factoring algorithm does. However, unlike factoring, which is in NP, it was unclear previously how to test the correctness of an approximation oracle for the permanent, and this is the contribution of the paper. The technical difficulty overcome here is that univariate polynomial self-correction, which underlies similar oracle-testing algorithms for permanent over finite fields --- and whose discovery led to a revolution in complexity theory --- does not seem to generalize to complex (or even, real) numbers. We believe that this tester will motivate further progress on understanding the permanent of Gaussian matrices.
Minimally Infrequent Itemset Mining using Pattern-Growth Paradigm and Residual Trees
Venue: arXiv cs.DB 2012
Year: 2012

Itemset mining has been an active area of research due to its successful application in various data mining scenarios including finding association rules. Though most of the past work has been on finding frequent itemsets, infrequent itemset mining has demonstrated its utility in web mining, bioinformatics and other fields. In this paper, we propose a new algorithm based on the pattern-growth paradigm to find minimally infrequent itemsets. A minimally infrequent itemset has no subset which is also infrequent. We also introduce the novel concept of residual trees. We further utilize the residual trees to mine multiple level minimum support itemsets where different thresholds are used for finding frequent itemsets for different lengths of the itemset. Finally, we analyze the behavior of our algorithm with respect to different parameters and show through experiments that it outperforms the competing ones.
Construction of zero autocorrelation stochastic waveforms
Venue: arXiv cs.IT 2012
Year: 2012

Stochastic waveforms are constructed whose expected autocorrelation can be made arbitrarily small outside the origin. These waveforms are unimodular and complex-valued. Waveforms with such spike like autocorrelation are desirable in waveform design and are particularly useful in areas of radar and communications. Both discrete and continuous waveforms with low expected autocorrelation are constructed. Further, in the discrete case, frames for the d-dimensional complex space are constructed from these waveforms and the frame properties of such frames are studied.
Learning Probabilistic Systems from Tree Samples
Venue: arXiv cs.LO 2012
Year: 2012

We consider the problem of learning a non-deterministic probabilistic system consistent with a given finite set of positive and negative tree samples. Consistency is defined with respect to strong simulation conformance. We propose learning algorithms that use traditional and a new "stochastic" state-space partitioning, the latter resulting in the minimum number of states. We then use them to solve the problem of "active learning", that uses a knowledgeable teacher to generate samples as counterexamples to simulation equivalence queries. We show that the problem is undecidable in general, but that it becomes decidable under a suitable condition on the teacher which comes naturally from the way samples are generated from failed simulation checks. The latter problem is shown to be undecidable if we impose an additional condition on the learner to always conjecture a "minimum state" hypothesis. We therefore propose a semi-algorithm using stochastic partitions. Finally, we apply the proposed (semi-) algorithms to infer intermediate assumptions in an automated assume-guarantee verification framework for probabilistic systems.
Algebraic on Magic Square of Odd Order n
Venue: arXiv cs.DM 2012
Year: 2012

This paper aims to address the relation between a magic square of odd order $n$ and a group, and their properties. By the modulo number $n$, we construct entries for each table from initial table of magic square with large number $n^2$. Generalization of the underlying idea is presented, we obtain unique group, and we also prove variants of the main results for magic cubes.
Primitive Words and Lyndon Words in Automatic and Linearly Recurrent Sequences
Venue: arXiv cs.FL 2012
Year: 2012

We investigate questions related to the presence of primitive words and Lyndon words in automatic and linearly recurrent sequences. We show that the Lyndon factorization of a k-automatic sequence is itself k-automatic. We also show that the function counting the number of primitive factors (resp., Lyndon factors) of length n in a k-automatic sequence is k-regular. Finally, we show that the number of Lyndon factors of a linearly recurrent sequence is bounded.
Meta-Learning of Exploration/Exploitation Strategies: The Multi-Armed Bandit Case
Venue: arXiv cs.AI 2012
Year: 2012

The exploration/exploitation (E/E) dilemma arises naturally in many subfields of Science. Multi-armed bandit problems formalize this dilemma in its canonical form. Most current research in this field focuses on generic solutions that can be applied to a wide range of problems. However, in practice, it is often the case that a form of prior information is available about the specific class of target problems. Prior knowledge is rarely used in current solutions due to the lack of a systematic approach to incorporate it into the E/E strategy. To address a specific class of E/E problems, we propose to proceed in three steps: (i) model prior knowledge in the form of a probability distribution over the target class of E/E problems; (ii) choose a large hypothesis space of candidate E/E strategies; and (iii), solve an optimization problem to find a candidate E/E strategy of maximal average performance over a sample of problems drawn from the prior distribution. We illustrate this meta-learning approach with two different hypothesis spaces: one where E/E strategies are numerically parameterized and another where E/E strategies are represented as small symbolic formulas. We propose appropriate optimization algorithms for both cases. Our experiments, with two-armed Bernoulli bandit problems and various playing budgets, show that the meta-learnt E/E strategies outperform generic strategies of the literature (UCB1, UCB1-Tuned, UCB-v, KL-UCB and epsilon greedy); they also evaluate the robustness of the learnt E/E strategies, by tests carried out on arms whose rewards follow a truncated Gaussian distribution.
Security Analysis of a Password-Based Authentication Protocol Proposed to IEEE 1363
Venue: arXiv cs.CR 2012
Year: 2012

In recent years, several protocols for password-based authenticated key exchange have been proposed. These protocols aim to be secure even though the sample space of passwords may be small enough to be enumerated by an off-line adversary. In Eurocrypt 2000, Bellare, Pointcheval and Rogaway (BPR) presented a model and security definition for authenticated key exchange. They claimed that in the ideal-cipher model (random oracles), the two-flow protocol at the core of Encrypted Key Exchange (EKE) is secure. Bellare and Rogaway suggested several instantiations of the ideal cipher in their proposal to the IEEE P1363.2 working group. Since then there has been an increased interest in proving the security of password-based protocols in the ideal-cipher model. For example, Bresson, Chevassut, and Pointcheval have recently showed that the One-Encryption-Key-Exchange (OEKE) protocol is secure in the ideal cipher model. In this paper, we present examples of real (NOT ideal) ciphers (including naive implementations of the instantiations proposed to IEEE P1363.2) that would result in broken instantiations of the idealised AuthA protocol and OEKE protocol. Our result shows that the AuthA protocol can be instantiated in an insecure way, and that there are no well defined (let alone rigorous) ways to distinguish between secure and insecure instantiations. Thus, without a rigorous metric for ideal-ciphers, the value of provable security in ideal cipher model is limited.
Least periods of k-automatic sequences
Venue: arXiv cs.FL 2012
Year: 2012

Currie and Saari initiated the study of least periods of infinite words, and they showed that every integer n >= 1 is a least period of the Thue-Morse sequence. We generalize this result to show that the characteristic sequence of least periods of a k-automatic sequence is (effectively) k-automatic. Through an implementation of our construction, we confirm the result of Currie and Saari, and we obtain similar results for the period-doubling sequence, the Rudin-Shapiro sequence, and the paperfolding sequence.
On the Non-robustness of Essentially Conditional Information Inequalities
Venue: arXiv cs.IT 2012
Year: 2012

We show that two essentially conditional linear inequalities for Shannon's entropies (including the Zhang-Yeung'97 conditional inequality) do not hold for asymptotically entropic points. This means that these inequalities are non-robust in a very strong sense. This result raises the question of the meaning of these inequalities and the validity of their use in practice-oriented applications.
Enhancing Data Security in Medical Information System Using the Watermarking Techniques and Oracle SecureFile LOBs
Venue: arXiv cs.CR 2012
Year: 2012

In this paper, we propose an efficient digital watermarking scheme to strengthen the security level already present in the database management system and to avoid illegal access to comprehensive content of database including patient's information. Doctors diagnose medical images by seeing Region of Interest (ROI). A ROI of a medical image is an area including important information and must be stored without any distortion. If a medical image is illegally obtained or if its content is changed, it may lead to wrong diagnosis. We substitute the part out of ROI of LSB bitplane of the image with the patient data and a binary feature map. This latter is obtained by extracting edges of the resized image to the quarter of its size using Laplacian operator. This image is directly integrated into the database. The edge map and invariant moments are used to check the integrity of the image.
Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation
Venue: arXiv cs.DB 2012
Year: 2012

In order to generate synthetic basket data sets for better benchmark testing, it is important to integrate characteristics from real-life databases into the synthetic basket data sets. The characteristics that could be used for this purpose include the frequent itemsets and association rules. The problem of generating synthetic basket data sets from frequent itemsets is generally referred to as inverse frequent itemset mining. In this paper, we show that the problem of approximate inverse frequent itemset mining is {\bf NP}-complete. Then we propose and analyze an approximate algorithm for approximate inverse frequent itemset mining, and discuss privacy issues related to the synthetic basket data set. In particular, we propose an approximate algorithm to determine the privacy leakage in a synthetic basket data set.
Exact Cramer-Rao Bounds for Semi-blind Channel Estimation in Amplify-and-Forward Two-Way Relay Networks
Venue: arXiv cs.IT 2012
Year: 2012

In this paper, we derive for the first time the exact Cramer-Rao bounds (CRBs) on semi-blind channel estimation for amplify-and-forward two-way relay networks. The bounds cover a wide range of modulation schemes that satisfy a certain symmetry condition. In particular, the important classes of PSK and square QAM are covered. For the case square QAM, we also provide simplified expressions that lend themselves more easily to numerical implementation. The derived bounds are used to show that the semi-blind approach, which exploits both the transmitted pilots and the transmitted data symbols, can provide substantial improvements in estimation accuracy over the training-based approach which only uses pilot symbols to estimate the channel parameters. We also derive the more tractable modified CRB which accurately approximates the exact CRB at high SNR for low modulation orders.